To date, every single NOAA, NASA, and IPCC Climate Model has gotten it wrong!

To counter this now obvious flaw, climate science agencies adopted the following strategy: utilize flashy marketing techniques when selling new “updated” climate models, focus media attention on supposedly once in-a-lifetime weather phenomenon, and most importantly, convince the public to patiently wait for the inevitable rise in global temperatures.

The ridiculous nature of this strategy is satirically portrayed in the photo above with an associated implied message here paraphrased as… just keep dressing yourself in a warm weather swimsuit even though there is snow on the ground, snow in the trees, and its cold outside. Not to worry, because eventually your warm weather dress attire will suit the climate. Shockingly for eighteen years the public has dutifully believed in this crazy climate science mandate....eventually the atmosphere will warm dramatically and man-made global warming computer models will be proven to be correct.

Malicious intent to mislead. Some of this is definitely occurring; however the problem goes deeper. Yes, politicians have carried things to the extreme when explaining / extolling climate models, but many hard working and very intelligent scientists have given it their best. They are not trying to mislead, they believe in their models.

Inexperienced incompetent scientists. No way! Lots of well-intentioned super nerds are working their hearts and minds out on this stuff.

Extremely flawed data. No again, kind of. Atmospheric data is accurate and abundant; however scientists have utilized just atmospheric data. Other data types such as geological and biological data have not been incorporated into the model-generation process.

Climate models built on effects, not causes. Bingo…winner winner chicken dinner! This is the main reason models have failed. Historically climate models have been purposely constructed in a fashion that matches observed “average” atmospheric climate trends, and resulting models work for a time, then fail. Why, because significant natural geological variations unexpectedly interrupt “average” atmospheric climate patterns. The length, intensity, and frequency of these natural geological variations cannot be modeled / predicted by using average atmospheric climate trends. Rather it is necessary to independently study the length, intensity, and frequency of these natural geological variations. Ongoing efforts to understand the role of natural geological forces on climate can be investigated by following visiting thePlate Climatology Theory page.

To help clarify this concept, the following is a geological example of how modelling the effects and not the cause can lead to model failure:

Let’s construct a model to predict fluid flow of geysers, specifically building a predictive model to explain water flow variations through a typical Yellowstone geyser. Geyser water flow variation is common in Yellowstone, but why?

One approach to building such a model would be to start by accurately measuring surface water temperatures, chemistry variations, flow-rate changes, biotic life-form changes / abundance, and mineral precipitation rates/types. After dutifully gathering mountains of said data, construction of the model begins by mathematically discerning average data trends: frequency, intensity, duration, etc. Done!

Now on to building a beautiful four-dimensional model (time is considered a fourth dimension) from this data, and performing final mathematical test runs. Awesome, works like a charm. So write up the press releases, make predictions, and wait for them to come true.

Big Problem! Given time the beautiful Yellowstone geyser model fails. What went wrong?

Turns out the surface water data was not directly related to, or necessarily indicative of, water flow variations in Yellowstone geysers. Upon further review, it’s discovered that geologically induced shifts in deep molten magma chambers are the root cause of geyser water flow variation. Using the abundant and accurate surface water flow data doomed the model to failure from the onset.

This is a classic case of modelling the effects, not the cause.

The same thing has happened with the NOAA, NASA and IPCC climate models. For years they have incorrectly constructed their climate models utilizing air fluid flow data at the exclusion of important natural geological data: heat and water flow from Deep Ocean rift systems, heat and water flow from major continental rift systems, and aerosol / particulate matter emissions from continental volcanoes. It should come as no surprise that their previous climate models have failed.

Finally, it just makes common sense that if major geological rift systems have the power to move entire continents 2-3 centimeters per year, frequently create large tsunamis that mix thousands of feet of ocean column, support vast chemo-synthetic communities, and contain 70% of the planets known active volcanoes, they can certainly and easily influence our climate in a dramatic fashion. Add to this the influence of continental volcanic emissions and it’s easy to understand why it’s long overdue to incorporate these geological forces into future climate models.